Page (U.S. Pat. No. 6,285,999 issued Sep. 4, 2001 to Lawrence Page, and entitled “Method for mode ranking in a linked database”) originally proposed a ranking measure referred to as PageRank. This ranking measure involved a node-to-node weight propagation scheme. The PageRank, or relative importance of a page (node), corresponds to a stationary distribution of probabilities. This probability distribution is that generated by a random walker surfing pages by randomly following out-links, or occasionally jumping to a random page. Page's method provides a static ranking of the popularity of pages independent of the query. But, in a typical application such as a search engine, there is a need to model the relevance of the query to a page while returning the ranked list of result pages.
The problem of ranking documents for a given query is also well studied. Several methods that consider document structure have been proposed. The HITS algorithm proposed by Kleinberg (U.S. Pat. No. 6,112,202 issued Aug. 29, 2000 to Jon Michael Kleinberg and entitled “Method and system for identifying authoritative information resources in an environment with content-based links between information resources”) requires access to a search engine, which returns a subset of results for a query. Their methods can then be used to select and rank relevant pages from these results. The main drawback of the Kleinberg's approach relates to performance. The time taken to retrieve the results, extract the links and perform the relevant link analysis, for each and every query is comparatively slow due to the computational demands associated with this activity.
Accordingly, a need exists in view of these and other observations, for an improved manner of ranking nodes and labels in a hyperlinked database.